An assessment approach for multi-state system mission reliability and success probability based on multi-resolution simulation

被引：0
|
作者：
Xu Y. [1 ]
Yang H. [1 ]
Lü J. [1 ]
Di P. [1 ]
机构：
[1] Department of Management Engineering and Equipment Economics, Naval University of Engineering, Wuhan
来源：
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2021年 / 41卷 / 05期
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
Mission reliability; Mission success probability; Monte Carlo simulation; Multi-resolution simulation; Multi-state system;
D O I：
10.12011/SETP2019-2632
中图分类号：
学科分类号：
摘要：
The problem of system mission reliability and success estimation under the condition of incomplete and uncertain information at different system levels in the early stage of weapon system development is studied. Through the resolution disaggregation mechanism of triggering random events layer by layer and the statistical value correction method of importance sampling, the fusion simulation of multi-resolution data at different system levels is realized. Additionally, through the accelerated sampling method such as forced transition and fault biasing under multi-resolution conditions, the sampling efficiency of small probability events is improved, and the sampling statistics are revised to ensure the unbiased estimation. By a case study of the ship system's navigation mission, the effectiveness of the multi-resolution simulation method is verified. It is found that the presented method improved simulation efficiency to different degrees for short task time and long task time. Based on the simulation sensitivity analysis, the influence of failure rate, repair rate and the type of maintenance time distribution on the system availability and mission success probability were evaluated. © 2021, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
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页码：1328 / 1342
页数：14
相关论文
共 16 条
  • [1] Bigelow J H, Davis P K., Implications of multi-resolution modeling (MRM) and exploratory analysis for validation, RAND, (1998)
  • [2] Davis P K, Tolk A., Observations on new developments in compensability and multi-resolution modeling, The 2007 Winter Simulation Conference, pp. 859-870, (2007)
  • [3] Yan F X, Li X M, Liu D, Et al., Cycle drive dynamic aggregation and disaggregation multi-resolution simulation model, Systems Engineering-Theory & Practice, 38, 6, pp. 1618-1632, (2018)
  • [4] Davis E R, Eckhause J M, Peterson D K, Et al., Exploring how hierarchical modeling and simulation can improve organizational resourcing decisions, Proceeding of Winter Simulation Conference, pp. 2496-2507, (2013)
  • [5] Zulch G, Jonsson U, Fischer J., Hierarchical simulation of complex production systems by coupling of models, International Journal of Production Economics, 77, 1, pp. 39-51, (2002)
  • [6] Hong S Y, Kim T G., Specification of multi-resolution modeling space for multi-resolution system simulation, Simulation: Transactions of the Society for Modeling and Simulation International, 89, 1, pp. 28-40, (2012)
  • [7] Rabelo L, Kim K, Park T W, Et al., Multi-resolution modeling, Proceeding of Winter Simulation Conference, pp. 2523-2534, (2015)
  • [8] Zhang W, Nie C L, Yu Y L, Et al., Aggregated model of equipment support simulation entity, Fire Control & Command Control, 38, 4, pp. 145-149, (2013)
  • [9] Xu Y F, Lu J W, Xie Z R, Et al., Multi-resolution risk assessment for complex system including technical risk, Journal of National University of Defence Technology, 40, 5, pp. 161-170, (2018)
  • [10] Jain S, Sigureardottir S, Lindskog E., Multi-resolution modeling for supply chain sustainability analysis, Proceeding of Winter Simulation Conference, pp. 1996-2007, (2013)
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